Computational studies of transcriptional activation domains
Max Staller, Assistant Researcher
Center for Computational Biology
Applications for Spring 2026 are closed for this project.
Transcription factors contain DNA binding domains and separate activation domains that bind coactivator complexes. DNA binding domains are conserved, structured and can be predicted from amino acid sequence. Activation domains are intrinsically disordered (they do not fold into a single 3D structure), poorly conserved and cannot be predicted from amino acid sequence. This project will apply modern computational tools to study activation domains.
Role: This is a purely computational project. You learn to run AlphaFold and AlphaFoldMetamer on activation domains and their coactivator partners. You will also apply other modern computational tools to activation domains, like FINCHES, or STARLING, or ALBATROSS. Time permitting, you will learn to run a collection of machine learning models for predicting activation domains from protein sequence. You will practice posing a hypothesis, testing it with the available data and revising the hypothesis. There will be an opportunity for explorative, self-directed data analysis.
Qualifications: Coursework in introductory biology. Computer programming in python. Any wet lab experience is useful but not necessary.
Hours: 9-11 hrs
Biological & Health Sciences